Algorithmic Bias and Data Visualization
Machine learning has enabled significant advancements in AI, but it is not possible to train machine learning models without vast amounts of high-quality data. Bias in a training data set—whether inherent in the data or introduced into the training data set—will result in a machine learning model that reflects that bias.
This webinar explores the risks of inadvertent algorithmic bias and strategies for addressing legal issues surrounding the use of data to train machines.
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